{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "#coding:utf-8\n",
    "#导入warnings包，利用过滤器来实现忽略警告语句。\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import missingno as msno\n",
    "\n",
    "Train_data = df_train1 = pd.read_csv(r'data\\train1.txt',sep='\\t')\n",
    "Test_data = df_test = pd.read_csv(r'data\\test.txt',sep='\\t')\n",
    "df_submit = pd.read_csv(r'data\\submit.txt',sep='\\t',header=None)\n",
    "df_train2 = pd.read_csv(r'data\\train2.txt',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6763"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_train2['updatePriceTimeJson']==\"{}\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train2['withdrawDate'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "Train_data['price_rate_new_old'] = Train_data['price']/Train_data['newprice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train2['total_time_temp'] = pd.to_datetime(df_train2['pullDate'])-pd.to_datetime(df_train2['pushDate'])\n",
    "df_train2['total_time'] = df_train2['total_time_temp'].apply(lambda x: x.days)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train2['not_sell'] = pd.to_datetime(df_train2['withdrawDate']).isnull().apply(lambda x: int(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.merge(df_train2,Train_data, how='left',on='cardid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Correlation of Numeric Features with Price'}>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 504x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f , ax = plt.subplots(figsize = (7, 7))\n",
    "\n",
    "plt.title('Correlation of Numeric Features with Price',y=1,size=16)\n",
    "\n",
    "sns.heatmap(data.corr(),square = True,  vmax=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data[['not_sell',]].corr()['not_sell'].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_train2['total_time'].value_counts().plot(kind='kde', legend=True, figsize=(20, 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data['price_rate_push_discount'] = Train_data['price']/data['pushPrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data.groupby('not_sell')['price_rate_new_old'].agg('mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data.corr()['total_time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data.corr('kendall')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data.corr('spearman') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='not_sell'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1440x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# data.groupby('race')['age'].mean()\n",
    "data.groupby('not_sell')['color'].value_counts().unstack().plot(kind='bar', figsize=(20, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='not_sell'>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "data.groupby('not_sell')['modelyear'].value_counts().unstack().plot(kind='bar', figsize=(20, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "not_sell\n",
       "0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "1    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "Name: mileage, dtype: object"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.groupby('not_sell')['mileage'].plot(kind='kde', legend=True, figsize=(20, 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pushPrice</th>\n",
       "      <th>mileage</th>\n",
       "      <th>price</th>\n",
       "      <th>newprice</th>\n",
       "      <th>price_rate_new_old</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>not_sell</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13.585651</td>\n",
       "      <td>7.289225</td>\n",
       "      <td>13.360855</td>\n",
       "      <td>28.474629</td>\n",
       "      <td>0.479561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14.844504</td>\n",
       "      <td>7.051915</td>\n",
       "      <td>14.700019</td>\n",
       "      <td>29.013670</td>\n",
       "      <td>0.526831</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          pushPrice   mileage      price   newprice  price_rate_new_old\n",
       "not_sell                                                               \n",
       "0         13.585651  7.289225  13.360855  28.474629            0.479561\n",
       "1         14.844504  7.051915  14.700019  29.013670            0.526831"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# from pandas.plotting import  table\n",
    "data.groupby('not_sell')[['pushPrice','mileage','price','newprice','price_rate_new_old']].agg(np.mean)\n",
    "# fig = plt.figure(figsize=(5, 6), dpi=1400)\n",
    "# ax = fig.add_subplot(111, frame_on=False) # no visible frame\n",
    "# ax.xaxis.set_visible(False)  # hide the x axis\n",
    "# ax.yaxis.set_visible(False)  # hide the y axis\n",
    "\n",
    "# table(ax, data.groupby('not_sell').agg(np.mean), loc='center')  # where df is your data frame\n",
    "\n",
    "# plt.savefig('correlation_matrix_HD.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_f = data[data['updatePriceTimeJson']!='{}'][data['not_sell']==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_json1(x):\n",
    "    import json\n",
    "    dic=json.loads(x)\n",
    "    return [list(dic.keys())[-1],list(dic.values())[-1]][0]\n",
    "def process_json2(x):\n",
    "    import json\n",
    "    dic=json.loads(x)\n",
    "    return [list(dic.keys())[-1],list(dic.values())[-1]][1]\n",
    "def process_json3(x):\n",
    "    import json\n",
    "    dic=json.loads(x)\n",
    "    return len(list(dic.keys()))\n",
    "# process_json('{\"2021-04-05\": \"23\"}')\n",
    "data_f['LastUpdateTime']=data_f['updatePriceTimeJson'].apply(process_json1)\n",
    "data_f['LastUpdatePrice']=data_f['updatePriceTimeJson'].apply(process_json2).apply(lambda x: float(x))\n",
    "data_f['LastUpdateTime']=pd.to_datetime(data_f['LastUpdateTime'])\n",
    "data_f['withdrawDate']=pd.to_datetime(data_f['withdrawDate'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2       2021-04-08\n",
       "4       2021-06-21\n",
       "5       2021-01-20\n",
       "10      2020-11-15\n",
       "13      2020-06-11\n",
       "           ...    \n",
       "7989    2020-12-09\n",
       "7992    2020-08-14\n",
       "7995    2021-06-12\n",
       "7996    2020-11-16\n",
       "7997    2020-08-19\n",
       "Name: withdrawDate, Length: 2696, dtype: object"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# data[data['updatePriceTimeJson']!='{}']['updatePriceTimeJson'].apply(process_json3).value_counts().plot(kind='bar', figsize=(10, 4))\n",
    "data_f['withdrawDate']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "modelyear\n",
       "2004.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2005.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2006.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2007.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2008.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2009.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2010.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2011.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2012.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2013.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2014.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2015.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2016.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2017.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2018.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2019.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2020.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "2021.0    AxesSubplot(0.125,0.125;0.775x0.755)\n",
       "Name: discount_rate, dtype: object"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_f.groupby('modelyear')['discount_rate'].plot(kind='kde', legend=True, figsize=(20, 5))\n",
    "# data.groupby('not_sell')['mileage'].plot(kind='kde', legend=True, figsize=(20, 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_f['afterUpdateSellTime']=(data_f['withdrawDate']-data_f['LastUpdateTime']).apply(lambda x : x.days)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>discount_rate</th>\n",
       "      <th>afterUpdateSellTime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>discount_rate</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>afterUpdateSellTime</th>\n",
       "      <td>0.020886</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     discount_rate  afterUpdateSellTime\n",
       "discount_rate             1.000000             0.020886\n",
       "afterUpdateSellTime       0.020886             1.000000"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_f['discount_rate']=data_f['LastUpdatePrice']/data_f['pushPrice']\n",
    "data_f[['discount_rate','afterUpdateSellTime']].corr('kendall')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data_f['discount_rate'].value_counts()\n",
    "# data_f.corr('spearman')['discount_rate'].plot(kind='bar', figsize=(20, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data_f['discount_rate']"
   ]
  }
 ],
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  "interpreter": {
   "hash": "a4a9b591a5d8c15248c8dae710090e12d42714cfc3a769cf18774ca735c05456"
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  "kernelspec": {
   "display_name": "Python 3.8.5 64-bit ('dl': conda)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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